Knowledge, Attitudes and Practices of Sanitation and Hygiene among Primary School Students in Rural Area of Northeast China

Disease burden due to unsafe water, lack of sanitation, and poor hygiene behavior requires attention. In developing countries, poor school hygiene behavior remains high-risk and causes infectious disease among students. Safe hygiene behavior such as hand washing with soap can protect children from infectious disease. However, a cross-sectional study found the correct rate of hand washing of Chinese people was only 4%. Our research evaluated the knowledge, attitudes, and practices (KAP) of sanitation and hygiene among school children in the rural area of Northeast China. Participants were 333 groups of students and their parents. A questionnaire was used in the participants who reported the score of KAP level of sanitation and hygiene. Hand washing skill was checked following a checklist. Observation of sanitation facilities at school was also conducted. The questionnaires included participant characteristic, household socioeconomic status, and KAP questionnaire. The results of the questionnaires survey showed more than 80% of students had adequate knowledge of proper hygiene. Although students have sufficient knowledge about hygiene, lack of facilities may negatively affect their practice. There was no soap available in 2 schools, 53% of students reported it affects their hand washing performance at school. The results indicated the impact of gender, facilities and knowledge level on behavior. Our findings underscore the need for more hygiene education and the improvement of sanitation and hygiene facilities in the area

Analysis of monitoring results of food microbial pathogenic factors in Zhoushan City from 2017 to 2019

Objective To understand the contamination status of microorganisms and pathogenic factors in 19 kinds of food in Zhoushan City, so as to provide basic data for food safety risk monitoring and early warning. Methods A total of 1 246 food samples were collected from 2017 to 2019 according to the requirements of the national risk monitor manual of food contamination and harmful factors from 2017 to 2019. The samples were tested for food microbial pathogenic factors. Results A total of 243 pathogenic factors were detected and the total detection rate was 19.50% (243/1 246). The detection rate of Salmonella in raw meat was 41.67% (30/72), the detection rate of Vibrio parahaemolyticus in bivalve shellfish was 31.58% (48/152), the detection rate of Anisakid in fresh marine fish was 27.00% (27/100), and the detection rate of Staphylococcus aureus in cold-made pastry was 16.25% (13/80). The detection rate of microorganism and its pathogenic factors in bulk food was higher than that in pre-packaged food. The difference was statistically significant (χ2=92.333, P<0.05). In different sampling locations, the highest detection rate of pathogenic factors was found in farmers’ markets (32.54%, 150/461), followed by online stores (25.44%, 29/114) and small restaurants (23.88%, 16/67). Conclusion From 2017 to 2019, 19 types of food on sale in Zhoushan City were contaminated by microorganisms and pathogenic factors at varying degrees. The contamination of microorganisms and pathogenic factors in take-out meals, raw animal meat and bivalve shellfish products was relatively serious. It is suggested to strengthen hygiene supervision on these types of food to prevent the occurrence of foodborne diseases

First-principles atomistic Wulff constructions for an equilibrium rutile TiO2 shape modeling

Identifying the exposed surfaces of rutile TiO2 crystal is crucial for its industry application and surface engineering. In this study, the shape of the rutile TiO2 was constructed by applying equilibrium thermodynamics of TiO2 crystals via first-principles density functional theory (DFT) and Wulff principles. From the DFT calculations, the surface energies of six low-index stoichiometric facets of TiO2 are determined after the calibrations of crystal structure. And then, combined surface energy calculations and Wulff principles, a geometric model of equilibrium rutile TiO2 is built up, which is coherent with the typical morphology of fully-developed equilibrium TiO2 crystal. This study provides fundamental theoretical guidance for the surface analysis and surface modification of the rutile TiO2-based materials from experimental research to industry manufacturing. (C) 2017 Elsevier B.V. All rights reserved

AI is a viable alternative to high throughput screening: a 318-target study

: High throughput screening (HTS) is routinely used to identify bioactive small molecules. This requires physical compounds, which limits coverage of accessible chemical space. Computational approaches combined with vast on-demand chemical libraries can access far greater chemical space, provided that the predictive accuracy is sufficient to identify useful molecules. Through the largest and most diverse virtual HTS campaign reported to date, comprising 318 individual projects, we demonstrate that our AtomNet® convolutional neural network successfully finds novel hits across every major therapeutic area and protein class. We address historical limitations of computational screening by demonstrating success for target proteins without known binders, high-quality X-ray crystal structures, or manual cherry-picking of compounds. We show that the molecules selected by the AtomNet® model are novel drug-like scaffolds rather than minor modifications to known bioactive compounds. Our empirical results suggest that computational methods can substantially replace HTS as the first step of small-molecule drug discovery

HectH9 hijacks glucose metabolism to fuel tumor growth

Our study uncovered that HectH9 drives glycolysis and tumor development by K63-linked ubiquitination of Hexokinase 2 (HK2). This mechanism is critical for HK2 localization to mitochondria for activating HK2’s functions in glycolysis promotion and apoptosis inhibition, suggesting that targeting HectH9 is a new strategy to tackle metabolism-addicted tumors

Prognostic Value of Basic Fibroblast Growth Factor (bFGF) in Lung Cancer: A Systematic Review with Meta-Analysis.

BACKGROUND:Basic fibroblast growth factor (bFGF) is known to stimulate angiogenesis and thus to influence the proliferation, migration and survival of tumor cells. Many studies examined the relationship between human bFGF overexpression and survival in lung cancer patients, but the results have been mixed. To systematically summarize the clinical prognostic function of bFGF in lung cancer, we performed this systematic review with meta-analysis. METHOD:Studies were identified by an electronic search of PubMed, EMBASE, China National Knowledge Infrastructure and Wanfang databases, including publications prior to August 2014. Pooled hazard ratios (HR) for overall survival (OS) were aggregated and quantitatively analyzed by meta-analysis. RESULTS:Twenty-two studies (n = 2154) were evaluated in the meta-analysis. Combined HR suggested that bFGF overexpression had an adverse impact on survival of patients with lung cancer(HR = 1.202,95%CI, 1.022-1.382). Our subgroup analysis revealed that the combined HR evaluating bFGF expression on OS in operable non-small cell lung cancer (NSCLC) was 1.553 (95%CI, 1.120-1.986); the combined HR in small cell lung cancer (SCLC) was 1.667 (95%CI, 1.035-2.299). There was no significant impact of bFGF expression on survival in advanced NSCLC. CONCLUSION:This meta-analysis showed that bFGF overexpression is a potential indicator of worse prognosis for patients with operable NSCLC and SCLC, but is not associated with outcome in advanced NSCLC. The data suggests that high bFGF expression is highly related to poor prognosis. Nevertheless,more high-quality studies should be performed in order to provide additional evidence for the prognostic value of bFGF in lung cancer